Applying Artificial Intelligence to Financial Investing

Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. While there are many subfields to artificial intelligence, this work seeks to identify the most commonly applied AI techniques to financial investing as appears in academic literature. AI techniques, such as knowledgebased, machine learning, and natural language processing, are integrated into systems that simultaneously address data identification, asset valuation, and risk management. Future trends will continue to integrate hybrid artificial intelligence techniques into financial investing, portfolio optimization, and risk management. The remainder of this chapter summarizes key contributions of applying AI to financial investing as appears in the academic literature.

[1]  Chun-Ling Chuang,et al.  Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction , 2013, Inf. Sci..

[2]  Nuno Horta,et al.  A SAX-GA approach to evolve investment strategies on financial markets based on pattern discovery techniques , 2013, Expert Syst. Appl..

[3]  Massimiliano Kaucic,et al.  Investment using evolutionary learning methods and technical rules , 2010, Eur. J. Oper. Res..

[4]  Akintunde Mutairu Oyewale.  Evaluation of artificial neural networks in foreign exchange forecasting , 2013 .

[5]  Tak-Chung Fu,et al.  Adopting genetic algorithms for technical analysis and portfolio management , 2013, Comput. Math. Appl..

[6]  Anupam Shukla,et al.  Analysis of Artificial Neural Network for Financial Time Series Forecasting , 2010 .

[7]  Vjekoslav Galzina,et al.  An adaptive network-based fuzzy inference system (ANFIS) for the forecasting: The case of close price indices , 2013, Expert Syst. Appl..

[8]  Stjepan Oreski,et al.  Genetic algorithm-based heuristic for feature selection in credit risk assessment , 2014, Expert Syst. Appl..

[9]  Maleerat Sodanil,et al.  Prediction of stock price using an adaptive Neuro-Fuzzy Inference System trained by Firefly Algorithm , 2013, 2013 International Computer Science and Engineering Conference (ICSEC).

[10]  R. K. Agrawal,et al.  A combination of artificial neural network and random walk models for financial time series forecasting , 2013, Neural Computing and Applications.

[11]  Germano C. Vasconcelos,et al.  Case-based reasoning combined with neural networks for credit risk analysis , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

[12]  Mu-Yen Chen,et al.  Predicting corporate financial distress based on integration of decision tree classification and logistic regression , 2011, Expert Syst. Appl..

[13]  Efstratios F. Georgopoulos,et al.  Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization , 2013, Eur. J. Oper. Res..

[14]  Gloria E. Phillips-Wren,et al.  Ai Tools in Decision Making Support Systems: a Review , 2012, Int. J. Artif. Intell. Tools.

[15]  Andries Petrus Engelbrecht,et al.  Carry trade portfolio optimization using particle swarm optimization , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[16]  Katia P. Sycara,et al.  Distributed Intelligent Agents , 1996, IEEE Expert.

[17]  Abdelwaheb Rebai,et al.  A fuzzy stochastic Goal Programming approach for solving portfolio selection problem , 2013, 2013 5th International Conference on Modeling, Simulation and Applied Optimization (ICMSAO).

[18]  David Semaan,et al.  Forecasting exchange rates: Artificial neural networks vs regression , 2014, International Conference on e-Technologies and Networks for Development.

[19]  Amaury Lendasse,et al.  Bankruptcy prediction using Extreme Learning Machine and financial expertise , 2014, Neurocomputing.

[20]  Chiun-Chieh Hsu,et al.  A hybrid approach to integrate genetic algorithm into dual scoring model in enhancing the performance of credit scoring model , 2012, Expert Syst. Appl..

[21]  Yannis Manolopoulos,et al.  Nonlinear multiple regression methods: a survey and extensions , 2010 .

[22]  Siddhartha Bhattacharyya,et al.  Knowledge-intensive genetic discovery in foreign exchange markets , 2002, IEEE Trans. Evol. Comput..

[23]  Tanja Magoc,et al.  The optimality of non-additive approaches for portfolio selection , 2011, Expert Syst. Appl..

[24]  Adrian Costea,et al.  Applying Fuzzy Logic and Machine Learning Techniques in Financial Performance Predictions , 2014 .

[25]  Jing J. Liang,et al.  Large-scale portfolio optimization using multiobjective dynamic mutli-swarm particle swarm optimizer , 2013, 2013 IEEE Symposium on Swarm Intelligence (SIS).

[26]  Robert Hudson,et al.  Herd behaviour experimental testing in laboratory artificial stock market settings. Behavioural foundations of stylised facts of financial returns , 2013 .

[27]  Arash Bahrammirzaee,et al.  A comparative survey of artificial intelligence applications in finance: artificial neural networks, expert system and hybrid intelligent systems , 2010, Neural Computing and Applications.

[28]  A. Victor Devadoss,et al.  Stock Prediction Using Artificial Neural Networks , 2013 .

[29]  Enriqueta Vercher,et al.  A multi-objective genetic algorithm for cardinality constrained fuzzy portfolio selection , 2012, Fuzzy Sets Syst..

[30]  Abdelouahid Lyhyaoui,et al.  Financial Intelligence in Prediction of Firm's Creditworthiness Risk: Evidence from Support Vector Machine Approach , 2013 .

[31]  Gwo-Hshiung Tzeng,et al.  DRSA-Based Neuro-Fuzzy Inference Systems for the Financial Performance Prediction of Commercial Banks , 2014 .

[32]  Yuan Xiao,et al.  The Research of Morphological Characteristics in Time Series of Stock Prices Based on CBR , 2013, 2013 Third International Conference on Intelligent System Design and Engineering Applications.

[33]  Chun-Ling Chuang,et al.  A hybrid neural network approach for credit scoring , 2011, Expert Syst. J. Knowl. Eng..

[34]  Mu-Yen Chen,et al.  A hybrid fuzzy time series model based on granular computing for stock price forecasting , 2015, Inf. Sci..

[35]  Martha Pulido,et al.  Particle swarm optimization of ensemble neural networks with fuzzy aggregation for time series prediction of the Mexican Stock Exchange , 2014, Inf. Sci..

[36]  Mu-Yen Chen,et al.  A hybrid ANFIS model for business failure prediction utilizing particle swarm optimization and subtractive clustering , 2013, Inf. Sci..

[37]  Jae Kwon Bae,et al.  Predicting financial distress of the South Korean manufacturing industries , 2012, Expert Syst. Appl..

[38]  Hasan Selim,et al.  A fuzzy rule based expert system for stock evaluation and portfolio construction: An application to Istanbul Stock Exchange , 2013, Expert Syst. Appl..

[39]  Davide La Torre,et al.  Financial portfolio management through the goal programming model: Current state-of-the-art , 2014, Eur. J. Oper. Res..

[40]  Xiao Liu,et al.  A DT-SVM Strategy for Stock Futures Prediction with Big Data , 2013, 2013 IEEE 16th International Conference on Computational Science and Engineering.

[41]  Adriano Lorena Inácio de Oliveira,et al.  A method for automatic stock trading combining technical analysis and nearest neighbor classification , 2010, Expert Syst. Appl..

[42]  Przemyslaw Grzegorzewski,et al.  Particle swarm intelligence tunning of fuzzy geometric protoforms for price patterns recognition and stock trading , 2013, Expert Syst. Appl..

[43]  Pasquale Lops,et al.  Financial Product Recommendation through Case-based Reasoning and Diversification Techniques , 2014, RecSys Posters.

[44]  Derya Avci,et al.  An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange , 2010, Expert Syst. Appl..

[45]  Filiz Özkan,et al.  Comparing the forecasting performance of neural network and purchasing power parity: The case of Turkey , 2013 .

[46]  Sahil Shah,et al.  Predicting stock market index using fusion of machine learning techniques , 2015, Expert Syst. Appl..

[47]  F. Mokhatab Rafiei,et al.  Financial health prediction models using artificial neural networks, genetic algorithm and multivariate discriminant analysis: Iranian evidence , 2011, Expert Syst. Appl..

[48]  Nikola Gradojevic,et al.  Fuzzy logic, trading uncertainty and technical trading , 2013 .

[49]  Roy Rada,et al.  Expert systems and evolutionary computing for financial investing: A review , 2008, Expert Syst. Appl..

[50]  Arun Agarwal,et al.  Recurrent neural network and a hybrid model for prediction of stock returns , 2015, Expert Syst. Appl..

[51]  Werner Kristjanpoller,et al.  Volatility forecast using hybrid Neural Network models , 2014, Expert Syst. Appl..

[52]  T. Yu,et al.  Performance analysis of Indian stock market index using neural network time series model , 2013, 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering.

[53]  Kotagiri Ramamohanarao,et al.  A HMM-based adaptive fuzzy inference system for stock market forecasting , 2013, Neurocomputing.

[54]  Michael Doumpos,et al.  Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms , 2013 .

[55]  Francisco Herrera,et al.  A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data , 2015, IEEE Transactions on Fuzzy Systems.

[56]  Bai Li,et al.  Research on WNN Modeling for Gold Price Forecasting Based on Improved Artificial Bee Colony Algorithm , 2014, Comput. Intell. Neurosci..

[57]  Tomasz Korol.  Early warning models against bankruptcy risk for Central European and Latin American enterprises , 2013 .

[58]  Fatos Xhafa,et al.  Utilizing artificial neural networks and genetic algorithms to build an algo-trading model for intra-day foreign exchange speculation , 2013, Math. Comput. Model..

[59]  Luis E. Zárate,et al.  Applying Artificial Neural Networks to prediction of stock price and improvement of the directional prediction index - Case study of PETR4, Petrobras, Brazil , 2013, Expert Syst. Appl..

[60]  Mohsen Akbari,et al.  Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization , 2014, Expert Syst. Appl..

[61]  Ying Zheng,et al.  Automated analysis and evaluation of SEC documents , 2014, 2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS).

[62]  Harry Eugene Stanley,et al.  Confidence and the Stock Market: An Agent-Based Approach , 2014, PloS one.

[63]  Iván Pastor Sanz,et al.  Bankruptcy visualization and prediction using neural networks: A study of U.S. commercial banks , 2015, Expert Syst. Appl..

[64]  Georgios Dounias,et al.  Bankruptcy prediction with neural logic networks by means of grammar-guided genetic programming , 2006, Expert Syst. Appl..

[65]  Pei-Chann Chang,et al.  Trend discovery in financial time series data using a case based fuzzy decision tree , 2011, Expert Syst. Appl..

[66]  Arash Ghanbari,et al.  Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting , 2010, Knowl. Based Syst..

[67]  Jae Kwon Bae,et al.  Using genetic algorithm based knowledge refinement model for dividend policy forecasting , 2012, Expert Syst. Appl..

[68]  Tingwen Huang,et al.  A One-Layer Recurrent Neural Network for Real-Time Portfolio Optimization With Probability Criterion , 2013, IEEE Transactions on Cybernetics.

[69]  Fei Wang,et al.  Combining technical trading rules using parallel particle swarm optimization based on Hadoop , 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

[70]  Kamaladdin Fataliyev,et al.  One-step and multi-step ahead stock prediction using backpropagation neural networks , 2013, 2013 9th International Conference on Information, Communications & Signal Processing.